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Category: Tools

Time Range Generation in Data Diluvium

Adron Hall extends Data Diluvium:

Following up on my previous posts about adding humidity and temperature data generation to Data Diluvium, I’m now adding a Time Range generator. I decided this would be a nice addition to give any graphing of the data a good look. This will complete the trio of generators I needed for my TimeScale DB setup. While humidity and temperature provide the environmental data, the Time Range generator ensures we have properly spaced time points for our time-series analysis.

Click through to see how it works.

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A New Dashboard for Distributed Availability Groups

David Fowler has been busy:

This comes off of the back of my last post looking at using a distributed availability group (DAG) to help facilitate a SQL server migration. SQL Server Migration Using a Distributed Availability Group

One thing that I mentioned in that post was that, although SSMS gives us a nice dashboard to check the health of our regular AGs. There’s nothing there to look at the state that the DAGs are in. The only choice that we’ve got is to tap up and compare results from a couple of DMVs on each side.

David has met that demand. Read on to see what the solution includes and how you can get your hands on it.

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The New Fabric CLI

Hasan Abo Shally announces a CLI:

  • The Fabric CLI is now in preview
  • It offers a developer-first, file-system-inspired way to explore and manage Microsoft Fabric
  • Use it interactively or script it into your workflows — from your terminal, in seconds
  • Built on Fabric APIs, designed for automation, and constantly evolving
  • Open source is on the horizon — with plans to empower the community to extend and shape the CLI

Give it a try. Break things. Tell us what you want next.

Click through for the full announcement. The idea here is to be the az cli for Fabric. Between this and Semantic Link Labs, it will make automating tasks in Microsoft Fabric easier.

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The Design of DataDiluvium

Adron Hall wraps up a series on DataDiluvium. First up is some commentary on data generation:

In Parts 1 and 2, I set up the development environment and implemented the schema parsing functionality. Now, I’ll explore the data generation system and final implementation details that make DataDiluvium a complete solution.

And finally we have some additional notes and wrapup:

In my previous three posts, I covered the core functionality of DataDiluvium. In this follow-up post, I’ll explore the additional features, utilities, and implementation details that I’ve added to enhance the application’s functionality and developer experience.

Check out both posts. I do enjoy seeing people walk through and explain some of the key concepts and decisions they’ve made when developing solutions.

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An Overview of DataDiluvium

Adron Hall has a new tool and a new blog series. The first post is a product overview:

DataDiluvium is a web-based tool available at datadiluvium.com that helps developers, database administrators, and data engineers generate realistic test data from SQL schema definitions. Whether you’re setting up a development environment, creating test scenarios, or preparing data for demonstrations, DataDiluvium streamlines the process of data generation.

The second covers some of the development precepts Adron used:

DataDiluvium is a web-based tool I’ve built designed to help developers, database administrators, and data engineers generate realistic test data based on SQL schema definitions. The tool takes SQL table definitions as input and produces sample data in various formats, making it easier to populate development and testing environments with meaningful data.

The tool is free, so if you’re looking for a sample data generator, check it out.

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Using the Excel Solver with Power Pivot

Chris Webb remembers a few functions:

After years of meaning to learn how to use Excel Solver, this week I’ve finally made a start: I want to use it to work out the optimal way of distributing workspaces across capacities in a Fabric tenant from the point of view of CU usage. I’m a long way from knowing how to do this properly (I’ll blog about it when I’m ready) but one of the first things I found is that while there are lots of resources on the internet showing how to use Solver, there are no examples of how to use Solver when your source data is stored in the Excel Data Model, aka Power Pivot. Getting that data onto the worksheet is fairly straightforward, but what if you also need Solver to change how that data is sliced and diced? It turns out that not hard to do if you know how to use cube functions.

Read on to see what Chris means and how you can send data from the Excel Data Model into the Solver.

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An Introduction to pgNow

Ryan Booz introduces a new free tool from Redgate:

pgNow is a free, cross-platform desktop tool created by Redgate that helps you identify key performance metrics and configuration optimizations in your running Postgres instance. Available now as a public preview application, it’s designed to help when you’re in a pinch and don’t have the Postgres experience or monitoring solution already in place to help identify why your server or database is experiencing a degradation in performance. Even in its current preview offering, pgNow is a helpful front-line tool for troubleshooting your Postgres cluster. And I couldn’t be more excited to share it with you.

Click through to see what’s in the preview. Ryan has mentioned that the tool will remain free even when it’s in a stable release.

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Visualizing PostgreSQL Query plans

MIchael Christofides views a plan:

When you’ve got a slow Postgres query, EXPLAIN and its parameters are incredibly useful for working out why.

However, the information returned can be difficult and time-consuming to interpret, especially for more complex queries. Over the years, people have built quite a few tools for visualizing Postgres query plans. As one of those people, I’m a little incredibly biased, but as a fan of many of the others, I hope to do them justice.

Read on for the options. I think the SQL Server world is a bit spoiled with Solarwinds Plan Explorer (even if the product hasn’t really changed since Solarwinds bought Sentry One), but some of these options look very solid.

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Orchestrating Data Pipelines in R with maestro

Will Hipson moves some data:

If you look at data orchestration tools today you are bombarded with a dizzying array of software platforms that claim unsurpassed processing capability, AI-readiness, elegant UIs, etc. Apache Airflow is just one example of a popular orchestration platform that scales to meet virtually any orchestration need. And while these claims may be true, I argue it is rarely the case that these gargantuan platforms are needed in the first place. For most data engineers, you probably only need to process a moderate amount of data at a moderate time scale. Moreover, if you’re an R user, you don’t want to have to define your data pipelines using drag-and-drop tools or learn another programming language. Not only will this reduce cloud costs but also development time costs.

Click through to see why Will developed maestro and how it works. H/T R-Bloggers.

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